Continuous functions on metric spaces part 2

In summary, "Continuous functions on metric spaces part 2" explores the properties and implications of continuity in the context of metric spaces. It delves into concepts such as uniform continuity, the relationship between continuous functions and compact spaces, and the behavior of continuous functions under various operations. The section emphasizes the importance of completeness and compactness in understanding continuity, illustrating these concepts with examples and theorems that highlight their significance in analysis and topology.
  • #1
Lambda96
223
75
Homework Statement
Show that the mapping ##x \mapsto d(x,p)## is linear.
Relevant Equations
none
Hi,

The task is as follows
Bildschirmfoto 2024-05-18 um 18.49.02.png


For the proof I wanted to use the boundedness, in the script of my professor the following is given, since both ##(X,d)## and ##\mathbb{R}## are normalized vector spaces

Bildschirmfoto 2024-05-18 um 16.21.50.png

I have now proceeded as follows ##|d(x,p)| \le C |x|## according to Archimedes' principle, a number ##C## now exists, which ensures that the inequality is valid for all ##x##.
 
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  • #2
##d(\cdot , p)## isn't linear.

Start with the definition of continuity. Use a function ##f## first, and substitute ##f(x)## with ##d(x,p)## afterwards. So: What does it mean, when a function ##f(x)## is continuous at ##x_0##?
 
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  • #3
fresh_42 said:
##d(\cdot , p)## isn't linear.

We are not even given that [itex]X[/itex] is a vector space, so we don't have a concept of linearity.

@Lambda96: All you have available to you are the properties of an arbitrary metric and the definition of continuity with respect to that metric. Consider the triangle rule.
 
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  • #4
Thank you fresh_42 and pasmith for your help 👍👍

The continuity of a function ##f## is defined as follows:

A function ##f## is called continuous at the point ##x_0## if for every ##\epsilon## there exists a ##\delta## such that for all ##x \in D_f## with ##|x-x_0| < \delta## : ##|f(x) - f(x_0)|< \epsilon## applies

Do you mean fresh_42 that I should now do the following?

$$|x-x_0| < \delta \rightarrow |d(x,p) - d(x_0,p)|< \epsilon$$

Then I should now determine the ##\delta##, right?
 
  • #5
Lambda96 said:
Thank you fresh_42 and pasmith for your help 👍👍

The continuity of a function ##f## is defined as follows:

A function ##f## is called continuous at the point ##x_0## if for every ##\epsilon## there exists a ##\delta## such that for all ##x \in D_f## with ##|x-x_0| < \delta## : ##|f(x) - f(x_0)|< \epsilon## applies

Do you mean fresh_42 that I should now do the following?

$$|x-x_0| < \delta \rightarrow |d(x,p) - d(x_0,p)|< \epsilon$$

Then I should now determine the ##\delta##, right?

Yes, and yes. Use @pasmith's hint. The triangle inequality is basically all we have. Note that ##|x-x_0|=d(x,x_0).##
 
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  • #6
Thank you fresh_42 for your help 👍


The triangle inequality is as follows ##d(x,x_0) \le d(x,p) + d(p,x_0)##


With the triangle inequality you can then set up the two inequalities ## d(x,p) - d(p,x_0) \le d(x,x_0)## and ## d(p,x_0)- d(x,p) \le d(x,x_0)## from this then follows ##|d(x,p) - (p,x_0)| \le d(x,x_0)##

The following ##|d(x,p)- d(p,x_0)| < \epsilon## holds and because of ##|d(x,p) - (p,x_0)| \le d(x,x_0)## with ##|x-x_0|=d(x,x_0)## then ##\delta=\epsilon## follows
 
  • #7
Lambda96 said:
Thank you fresh_42 for your help 👍


The triangle inequality is as follows ##d(x,x_0) \le d(x,p) + d(p,x_0)##


With the triangle inequality you can then set up the two inequalities ## d(x,p) - d(p,x_0) \le d(x,x_0)## and ## d(p,x_0)- d(x,p) \le d(x,x_0)## from this then follows ##|d(x,p) - (p,x_0)| \le d(x,x_0)##

The following ##|d(x,p)- d(p,x_0)| < \epsilon## holds and because of ##|d(x,p) - (p,x_0)| \le d(x,x_0)## with ##|x-x_0|=d(x,x_0)## then ##\delta=\epsilon## follows
I'll make this general comment for the last time. You are not thinking through these problems in terms of what you are trying to prove. Your work is superficial, IMO. It's not that you need detail, as such, but that you need to be much clearer about the steps required in the proof.

In this case, specifically, you didn't say that for a function to be continuous, we mean that it is continuous at every point ##x_0 \in X##. You might say you knew that. But, I'm not convinced that you recognised that.

So, your proof should start: "Let ##x_0 \in X## and ##\epsilon > 0##.

PS Having a coherent, logical structure to your proof is a good habit to get into.
 
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  • #8
Thanks PeroK for the tip 👍

Unfortunately, I forgot to say in my calculation that I was only interested with the calculation of how to determine the ##\delta##. In my documents I have provided complete proof
 
  • #9
In fact we have uniform continuity, since [itex]\delta = \epsilon[/itex] works independently of [itex]x[/itex].
 
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FAQ: Continuous functions on metric spaces part 2

What is a continuous function on a metric space?

A continuous function on a metric space is a function f: X → Y between two metric spaces (X, d_X) and (Y, d_Y) such that for every point x in X and for every ε > 0, there exists a δ > 0 such that if d_X(x, x') < δ, then d_Y(f(x), f(x')) < ε. This means that small changes in the input lead to small changes in the output.

How do we define continuity in terms of open sets?

A function f: X → Y between metric spaces is continuous if for every open set V in Y, the preimage f^(-1)(V) is an open set in X. This topological definition of continuity aligns with the ε-δ definition and provides a more general framework that can be applied to other types of spaces beyond metric spaces.

What is the relationship between continuous functions and compactness?

Continuous functions preserve compactness. Specifically, if X is a compact metric space and f: X → Y is a continuous function, then the image f(X) is also compact in Y. This property is particularly useful in analysis and topology, as it allows us to extend results from compact spaces to their images under continuous mappings.

Can a continuous function on a metric space be uniformly continuous?

Yes, a continuous function on a metric space can be uniformly continuous, but not all continuous functions are uniformly continuous. A function f: X → Y is uniformly continuous if for every ε > 0, there exists a δ > 0 such that for all x, x' in X, if d_X(x, x') < δ, then d_Y(f(x), f(x')) < ε. Uniform continuity is a stronger condition than continuity and is particularly important in the context of complete metric spaces.

What are some examples of continuous functions on metric spaces?

Examples of continuous functions on metric spaces include the identity function f(x) = x on any metric space, polynomial functions defined on the real numbers with the standard metric, and the exponential function f(x) = e^x. Additionally, any function that is Lipschitz continuous is also continuous, and functions that map compact sets to Hausdorff spaces are continuous as well.

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